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ARTIFICIAL INTELLIGENCE + ROBOTS #1 (The Cognitive Computing Age (2020s…
ARTIFICIAL INTELLIGENCE + ROBOTS #1
What is AI?
AI is a software that can do cognitive work
Machines that mimic "cognitive" functions that humans associate w/ the human mind, such as learning + problem-solving
AI systems will typically demonstrate at least some of the following behaviours associated w/ human intelligence: planning, learning, reasoning, problem solving, perception etc
Many other aspects of technology, such as Big Data, can't happen without AI
Three Approaches to AI
Codified Rules [e.g Expert Systems]
In AI, an expert system is a computer system that emulates the decision-making ability of a human expert
Heuristics + Evolutionary Learning
A heuristic is a technique designed for solving a problem more quickly when classic methods are too slow, for example. It's achieved by trading accuracy + optimality for speed
Can be considered a 'shortcut'
Evolutionary learning: models constructed based on aspects of evolution, as observed in biology
Artificial Neural Networks + Deep Learning
ANNs are multi-layer fully-connected neural nets, which consist of an input layer, multiple hidden layers + an output layer
We make the network deeper by increasing the no. of hidden layers
Deep learning is a class of machine learning algorithms that use multiple layers to progressively extract higher level features from the raw input
E.g image processing: lower layers may identify edges while higher layers may identify the concepts relevant to a human such as digits/letters/faces
ANNs/Deep Learning are the most common form
A Deep Learning ANN
Deep learning is a subfield of machine learning concerned w/ algorithms inspired by the structure + function of the brain called artificial neural networks
The core of deep learning is that we now have fast enough computers + enough data to actually train large neural networks [Andrew Ng - founder of Google Brain]
A neural network is loads of artificial neurons
It's called deep learning bc in the middle of the diagram there are lots of layers of artificial neurons between the input + the output that don't necessarily know what's going on
The Cognitive Computing Age
Before 1980s: Early Computing.
Computing was rare, expensive + required a lot of skill
1980s-2000s: Personal Computing
2000s-2020s: Network Computing.
Value add was largely through communication
2020s-2040s: Cognitive Computing
The use of computerised models to stimulate the human thought process in complex situations where the answer may be uncertain/ambiguous
Overlaps w/ AI + involves many of the same underlying technologies to power cognitive applications, including expert systems, neural networks + robotics
Most digital tech will be able to possess or remotely access AI
Machine Learning [ML] will increasingly automate prediction
2040s-2060s: Cyborg Fusion.
This will facilitate a transition towards attentive computing: a world where the machine will attend to us
The AI Trojan Horses
Smart speakers like Alexa get people used to having omnipresent computing interfaces all around them
Companies want their intangible interfaces everywhere, so they can learn everything about people + provide personalised experiences
Decide the value of individuals based on fervid information processing - computer-driven scoring allows 'practical' discriminations that separate those who don't count from those who do, + price accordingly
Cloud AI Services
Can by AI over the internet pay-as-you-go: any company that wants to use it now can
IBM: the fusion of AI and Cloud Computing "promises to be both a source of innovation and a means to accelerate change"
The cloud can help provide AIs w/ the info they need to learn, while the AIs can generate new info + insights which gives the cloud more data
Cloud AI in Context
10 years ago, the potential operational + strategic reasons to cloud compute were:
Cost reduction + transformation [fixed to variable]
Lowering/migration of IT carbon footprint
To prepare to leverage next generation cloud services
And with the delivery of cloud AI, these next generation services have now arrived
If companies don't start using cloud services now, they won't be prepared for the next generation
Key [Western] Market Players
Amazon w/ Machine Learning on AWS
IBM w/ Watson
Google Cloud AI on the Google Cloud Platform
Microsoft w/ Azure Cognitive Services